{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b1e515ac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple/\n",
      "Requirement already satisfied: baostock in c:\\users\\yzx\\anaconda3\\lib\\site-packages (0.8.8)\n",
      "Requirement already satisfied: pandas>=0.18.0 in c:\\users\\yzx\\anaconda3\\lib\\site-packages (from baostock) (1.4.4)\n",
      "Requirement already satisfied: python-dateutil>=2.8.1 in c:\\users\\yzx\\anaconda3\\lib\\site-packages (from pandas>=0.18.0->baostock) (2.8.2)\n",
      "Requirement already satisfied: numpy>=1.18.5 in c:\\users\\yzx\\anaconda3\\lib\\site-packages (from pandas>=0.18.0->baostock) (1.21.5)\n",
      "Requirement already satisfied: pytz>=2020.1 in c:\\users\\yzx\\anaconda3\\lib\\site-packages (from pandas>=0.18.0->baostock) (2022.1)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\yzx\\anaconda3\\lib\\site-packages (from python-dateutil>=2.8.1->pandas>=0.18.0->baostock) (1.16.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install baostock -i https://pypi.tuna.tsinghua.edu.cn/simple/ --trusted-host pypi.tuna.tsinghua.edu.cn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "990a57fd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "login success!\n",
      "login respond error_code:0\n",
      "login respond  error_msg:success\n",
      "query_history_k_data_plus respond error_code:0\n",
      "query_history_k_data_plus respond  error_msg:success\n",
      "           date       code        open        high         low       close  \\\n",
      "0    2020-01-02  sz.399997   8301.0880   8389.5750   8200.7240   8315.0160   \n",
      "1    2020-01-03  sz.399997   8298.4330   8323.8260   8185.6940   8219.7300   \n",
      "2    2020-01-06  sz.399997   8181.2270   8242.8550   8103.2620   8150.7970   \n",
      "3    2020-01-07  sz.399997   8153.9880   8253.9260   8147.8590   8241.0400   \n",
      "4    2020-01-08  sz.399997   8214.3220   8293.7660   8194.4230   8254.5330   \n",
      "..          ...        ...         ...         ...         ...         ...   \n",
      "750  2023-02-09  sz.399997  16279.6101  16862.2331  16270.0593  16816.4758   \n",
      "751  2023-02-10  sz.399997  16798.0123  17027.7153  16714.3475  16893.3161   \n",
      "752  2023-02-13  sz.399997  16857.8915  17756.0908  16857.8915  17550.3352   \n",
      "753  2023-02-14  sz.399997  17547.6530  17751.5983  17357.8447  17424.7797   \n",
      "754  2023-02-15  sz.399997  17474.5634  17654.4314  17354.0829  17416.3122   \n",
      "\n",
      "       preclose     volume            amount adjustflag      turn tradestatus  \\\n",
      "0     8406.6230  186436427  26950355712.0000          3  1.152400           1   \n",
      "1     8315.0160  144790804  21871442176.0000          3  0.894980           1   \n",
      "2     8219.7300  137737277  15035809024.0000          3  0.891908           1   \n",
      "3     8150.7970  137434283  12497966080.0000          3  0.000000           1   \n",
      "4     8241.0400  120905932   9445235968.0000          3  0.747343           1   \n",
      "..          ...        ...               ...        ...       ...         ...   \n",
      "750  16305.4549  228436262  24454533733.7700          3  1.322100           1   \n",
      "751  16816.4758  210979956  19277085458.5600          3  1.221070           1   \n",
      "752  16893.3161  308431049  34515790653.7100          3  1.785079           1   \n",
      "753  17550.3352  219988225  22168070636.2800          3  1.273206           1   \n",
      "754  17424.7797  203477888  18980209637.6500          3  1.177651           1   \n",
      "\n",
      "        pctChg isST  \n",
      "0    -1.089700    0  \n",
      "1    -1.145951    0  \n",
      "2    -0.838629    0  \n",
      "3     1.107168    0  \n",
      "4     0.163729    0  \n",
      "..         ...  ...  \n",
      "750   3.134049    0  \n",
      "751   0.456935    0  \n",
      "752   3.889225    0  \n",
      "753  -0.715402    0  \n",
      "754  -0.048595    0  \n",
      "\n",
      "[755 rows x 14 columns]\n",
      "logout success!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<baostock.data.resultset.ResultData at 0x19de5ebf760>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import baostock as bs\n",
    "import pandas as pd\n",
    "\n",
    "#### 登陆系统 ####\n",
    "lg = bs.login()\n",
    "# 显示登陆返回信息\n",
    "print('login respond error_code:'+lg.error_code)\n",
    "print('login respond  error_msg:'+lg.error_msg)\n",
    "\n",
    "#### 获取沪深A股历史K线数据 ####\n",
    "# 详细指标参数，参见“历史行情指标参数”章节；“分钟线”参数与“日线”参数不同。“分钟线”不包含指数。\n",
    "# 分钟线指标：date,time,code,open,high,low,close,volume,amount,adjustflag\n",
    "# 周月线指标：date,code,open,high,low,close,volume,amount,adjustflag,turn,pctChg\n",
    "rs = bs.query_history_k_data_plus(\"sz.399997\",\n",
    "    \"date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,isST\",\n",
    "    start_date='2020-01-01', end_date='2023-02-15',\n",
    "    frequency=\"d\", adjustflag=\"3\")\n",
    "print('query_history_k_data_plus respond error_code:'+rs.error_code)\n",
    "print('query_history_k_data_plus respond  error_msg:'+rs.error_msg)\n",
    "\n",
    "#### 打印结果集 ####\n",
    "data_list = []\n",
    "while (rs.error_code == '0') & rs.next():\n",
    "    # 获取一条记录，将记录合并在一起\n",
    "    data_list.append(rs.get_row_data())\n",
    "result = pd.DataFrame(data_list, columns=rs.fields)\n",
    "\n",
    "#### 结果集输出到csv文件 ####   \n",
    "result.to_csv(\"history_A_stock_k_data.csv\", index=False)\n",
    "print(result)\n",
    "\n",
    "#### 登出系统 ####\n",
    "bs.logout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a003abd6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x19de60b0f70>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result['open'].astype(float).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "34ca647e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
